Complex network community mining method based on cellular automatic learning machine

Abstract

The invention discloses a complex network community mining method based on a cellular automatic learning machine. The method comprises the six steps of initializing the cellular automatic learning machine, generating state vectors of the cellular automatic learning machine, decoding the state vectors of the cellular automatic learning machine to obtain the corresponding communities, calculating response signals, updating the cellular automatic learning machine, and comparing community structures. According to the complex network community mining method, the whole network is modeled into the cellular automatic learning machine, the communities in the network are mapped into the state vectors of the cellular automatic learning machine, and the network is searched for the optimal community structure through iterative updating of the cellular automatic learning machine. The complex network community mining method is quite low in time complexity and applicable to a large-scale complex network. In addition, the complex network community mining method has the good performance for searching for the globally optimal solution, and can ensure compactness of local communities, so that community detection precision is quite high.

Description

technical field [0001] The invention relates to the technical field of complex network community mining, in particular to a complex network community mining method based on a cellular automatic learning machine. Background technique [0002] A complex network is an abstract representation of complex systems in the real world. The nodes in the network represent the individuals in the system, and the connections between nodes represent the interrelationships between the individuals in the system. At present, complex networks have been widely used to characterize various complex systems such as power networks, communication networks, Internet networks, social networks, neural networks, and protein networks. [0003] Community structure is an important topological characteristic of complex networks. The entire complex network is composed of several communities. The nodes within each community are very closely connected, while the connections between communities are relatively sp...

AI Technical Summary

Problems solved by technology

This scheme uses the local optimal solution search, which greatly improves the detection accuracy, but also increases the complexity of the method; at the same time, because the closeness of the local community structure is ignored, the obtained communities often contain unreasonable communities.

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